One of the main challenges in materials discovery is efficiently exploring the vast search
space for targeted properties as approaches that rely on trial-and-error are impractical. We …

A key aspect of the developing field of materials informatics is optimally guiding experiments
or calculations towards parts of the relatively vast feature space where a material with …

Network biology, an interdisciplinary field at the intersection of computational and biological
sciences, is critical for deepening understanding of cellular functioning and disease. While …

In this paper, we propose a general experimental design framework for optimally guiding
new experiments or simulations in search of new materials with desired properties. The …

In many contemporary engineering problems, model uncertainty is inherent because
accurate system identification is virtually impossible owing to system complexity or lack of …

Molecular design based on generative models, such as variational autoencoders (VAEs),
has become increasingly popular in recent years due to its efficiency for exploring high …

Significant acceleration of the future discovery of novel functional materials requires a
fundamental shift from the current materials discovery practice, which is heavily dependent …

In many practical filter design problems, the exact statistical information of the underlying
random processes is not available. One robust filtering approach in these situations is to …

We derive robust linear filtering and experimental design for systems governed by stochastic
differential equations (SDEs) under model uncertainty. Given a model of signal and …

Plant Synthetic Biology: Quantifying the “Known Unknowns” and Discovering the “Unknown
Unknowns” | Plant Physiology | Oxford Academic Skip to Main Content Advertisement Oxford …